Biologically based modeling of multimedia, multipathway, multiroute population exposures to arsenic

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

Consumer health risk assessment of Arsenic and Mercury in hen eggs through Monte Carlo simulations

BACKGROUND

This study was conducted to assess the concentration of heavy metals (arsenic and mercury) and estimate the probability that consumption of hen egg products collected in Iran has carcinogenic or non-carcinogenic consequences.

METHODS

A total of eighty-four hen eggs from 21 major brands were randomly selected from among thirty local supermarkets in two seasons (winter (January) and summer (August) 2022). Arsenic (As) and Mercury (Hg) was determined by using ICP-MS. The human health risk assessment refers to the formulation of the USEPA standard focused on Estimated Daily Intake (EDI), International Lifetime Cancer Risk (ILCR), Target Hazard Quotient (THQ), and Monte Carlo simulation (MCS) as a probabilistic method. Data analysis was carried out using the statistical software SPSS. Differences in mean concentrations of As and Hg in two seasons were tested by paired t-test.

RESULTS

Over two seasons, the average As and Hg concentrations in hen eggs were 0.79 and 0.18 µg.kg^-1, respectively. Seasonal difference in As concentration (p = 0.451) was not significant, whereas that of Hg concentration (p < 0.001) was significant. The calculated value of EDI was 0.29 µg As/day and 0.06 µg Hg/day. The EWI in the maximum scenario of as level in hen eggs was estimated to be 8.71 µg As and 1.89 µg Hg/month for Iranian adults. THQ's mean for As and Hg in adults was determined to be 0.00385 and 0.00066, respectively. In addition, ILCRs by MCS for As were 4.35E-4.

CONCLUSION

In total, the result indicates that there was not a significant risk of developing cancer; the calculation of THQ was still below the accepted level of 1, indicating that there was no risk while, according to most regulatory programs (ILCR > 10^- 4) shows a threshold carcinogenic risk of arsenic through consuming in hen eggs. Therefore, policymakers need to be aware that it is prohibited to establish chicken farms in heavily polluted urban areas. It is essential to regularly conduct examinations to measure the presence of heavy metals in both ground waters used for agriculture and the feed provided to chickens. Additionally, it is advisable to focus on raising public awareness about the importance of maintaining a healthy diet.

Probability of Non-Exceedance of Arsenic Concentration in Groundwater Estimated Using Stochastic Multicomponent Reactive Transport Modeling

Stochastic multicomponent reactive transport modeling is a powerful approach to quantify the probability of non-exceedance (PNE) of arsenic (As) critical concentration thresholds in groundwater. The approach is applied to a well-characterized shallow alluvial aquifer near Venice, Italy. Here, As mobility depends primarily on rainfall-controlled redox-dependent precipitation-dissolution of iron hydroxides. A Monte-Carlo analysis based on a calibrated three-dimensional flow and transport model targeted the geochemical initial conditions as the main source of uncertainty of As concentrations in the studied aquifer. It was found that, during 115 simulated days, the fraction of the entire aquifer volume with As > 10 μgL−1 decreased on average from ~43% to ~39% and the average As concentration from ~32 μgL−1 to ~27 μgL−1. Meanwhile, PNE increased from 55% to 60% when 10 μgL−1 was set as target threshold, and from 71% to 78% for 50 μgL−1. The time dependence of As attenuation can be ascribed to the increase of oxidizing conditions during rainfall-dependent aquifer recharge, which causes As sorption on precipitating iron hydroxides. When computing the same statistics for the shallowest 6 m, As attenuation was even more evident. The volume fraction of aquifer with As > 10μgL−1 dropped from 40% to 28% and the average As concentration from 31 μgL−1 to 20 μgL−1, whereas PNE increased from 58% to 70% for As < 10 μgL−1 and from 71% to 86% for As < 50 μgL−1. Thus, the wells screen depth in the aquifer can be a critical aspect when estimating As risk, owing to the depth-dependent relative change in redox conditions during rainfall events.

Arsenic toxicokinetic modeling and risk analysis: Progress, needs and applications

Arsenic (As) poses unique challenges in PBTK model development and risk analysis applications. Arsenic metabolism is complex, adequate information to attribute specific metabolites to particular adverse effects in humans is sparse, and measurement of relevant metabolites in biological media can be difficult. Multiple As PBTK models have been published and used or adapted for use in various exposure and risk analysis applications. These applications illustrate the broad utility of PBTK models for exposure and dose-response analysis, particularly for arsenic where multi-pathway, multi-route exposures and multiple toxic effects are of concern. Arsenic PBTK models have been used together with exposure reconstruction and dose-response functions to estimate risk of specific adverse health effects due to drinking water exposure and consumption of specific foodstuffs (e.g. rice, seafood), as well as to derive safe exposure levels and develop consumption advisories. Future refinements to arsenic PBTK models can enhance the confidence in such analyses. Improved estimates for methylation biotransformation parameters based on in vitro to in vivo extrapolation (IVIVE) methods and estimation of interindividual variability in key model parameters for specific toxicologically relevant metabolites are two important areas for consideration.

Development of a generic lifelong physiologically based biokinetic model for exposome studies

The current study within the frame of the HEALS project aims at the development of a lifelong physiologically based biokinetic (PBBK) model for exposome studies. The aim was to deliver a comprehensive modelling framework for addressing a large chemical space. Towards this aim, the delivered model can easily adapt parameters from existing ad-hoc models or complete the missing compound specific parameters using advanced quantitative structure activity relationship (QSAR). All major human organs are included, as well as arterial, venous, and portal blood compartments. Xenobiotics and their metabolites are linked through the metabolizing tissues. This is mainly the liver, but also other sites of metabolism might be considered (intestine, brain, skin, placenta) based on the presence or not of the enzymes involved in the metabolism of the compound of interest. Each tissue is described by three mass balance equations for (a) red blood cells, (b) plasma and interstitial tissue and (c) cells respectively. The anthropometric parameters of the models are time dependent, so as to provide a lifetime internal dose assessment, as well as to describe the continuously changing physiology of the mother and the developing fetus. An additional component of flexibility is that the biokinetic processes that relate to metabolism are related with either Michaelis-Menten kinetics, as well as intrinsic clearance kinetics. The capability of the model is demonstrated in the assessment of internal exposure and the prediction of expected biomonitored levels in urine for three major compounds within the HEALS project, namely bisphenol A (BPA), Bis(2-ethylhexyl) phthalate (DEHP) and cadmium (Cd). The results indicated that the predicted urinary levels fit very well with the ones from human biomonitoring (HBM) studies; internal exposure to plasticizers is very low (in the range of ng/L), while internal exposure to Cd is in the range of μg/L.

Critical assessment and integration of separate lines of evidence for risk assessment of chemical mixtures

Humans are exposed to multiple chemicals on a daily basis instead of to just a single chemical, yet the majority of existing toxicity data comes from single-chemical exposure. Multiple factors must be considered such as the route, concentration, duration, and the timing of exposure when determining toxicity to the organism. The need for adequate model systems (in vivo, in vitro, in silico and mathematical) is paramount for better understanding of chemical mixture toxicity. Currently, shortcomings plague each model system as investigators struggle to find the appropriate balance of rigor, reproducibility and appropriateness in mixture toxicity studies. Significant questions exist when comparing single-to mixture-chemical toxicity concerning additivity, synergism, potentiation, or antagonism. Dose/concentration relevance is a major consideration and should be subthreshold for better accuracy in toxicity assessment. Previous work was limited by the technology and methodology of the time, but recent advances have resulted in significant progress in the study of mixture toxicology. Novel technologies have added insight to data obtained from in vivo studies for predictive toxicity testing. These include new in vitro models: omics-related tools, organs-on-a-chip and 3D cell culture, and in silico methods. Taken together, all these modern methodologies improve the understanding of the multiple toxicity pathways associated with adverse outcomes (e.g., adverse outcome pathways), thus allowing investigators to better predict risks linked to exposure to chemical mixtures. As technology and knowledge advance, our ability to harness and integrate separate streams of evidence regarding outcomes associated with chemical mixture exposure improves. As many national and international organizations are currently stressing, studies on chemical mixture toxicity are of primary importance.

Physiology-based toxicokinetic modelling in the frame of the European Human Biomonitoring Initiative

Given the opportunities provided by internal dosimetry modelling in the interpretation of human biomonitoring (HBM) data, the assessment of the links between exposure to chemicals and observed HBM data can be effectively supported by PBTK modelling. This paper gives a comprehensive review of available human PBTK models for compounds selected as a priority by the European Human Biomonitoring Initiative (HBM4EU). We highlight their advantages and deficiencies and suggest steps for advanced internal dose modelling. The review of the available PBTK models highlighted the conceptual differences between older models compared to the ones developed recently, reflecting commensurate differences in research questions. Due to the lack of coordinated strategies for deriving useful biomonitoring data for toxicokinetic properties, significant problems in model parameterisation still remain; these are further increased by the lack of human toxicokinetic data due to ethics issues. Finally, questions arise as well as to the extent they are really representative of interindividual variability. QSARs for toxicokinetic properties is a complementary approach for PBTK model parameterisation, especially for data poor chemicals. This approach could be expanded to model chemico-biological interactions such as intestinal absorption and renal clearance; this could serve the development of more complex generic PBTK models that could be applied to newly derived chemicals. Another gap identified is the framework for mixture interaction terms among compounds that could eventually interact in metabolism. From the review it was concluded that efforts should be shifted toward the development of generic multi-compartmental and multi-route models, supported by targeted biomonitoring coupled with parameterisation by both QSAR approach and experimental (in-vivo and in-vitro) data for newly developed and data poor compounds.

Evaluation of a Physiologically Based Pharmacokinetic (PBPK) Model for Inorganic Arsenic Exposure Using Data from Two Diverse Human Populations

BACKGROUND

Multiple epidemiological studies exist for some of the well-studied health endpoints associated with inorganic arsenic (iAs) exposure; however, results are usually expressed in terms of different exposure/dose metrics. Physiologically based pharmacokinetic (PBPK) models may be used to obtain a common exposure metric for application in dose-response meta-analysis.

OBJECTIVE

A previously published PBPK model for inorganic arsenic (iAs) was evaluated using data sets for arsenic-exposed populations from Bangladesh and the United States.

METHODS

The first data set was provided by the Health Effects of Arsenic Longitudinal Study cohort in Bangladesh. The second data set was provided by a study conducted in Churchill County, Nevada, USA. The PBPK model consisted of submodels describing the absorption, distribution, metabolism and excretion (ADME) of iAs and its metabolites monomethylarsenic (MMA) and dimethylarsenic (DMA) acids. The model was used to estimate total arsenic levels in urine in response to oral ingestion of iAs. To compare predictions of the PBPK model against observations, urinary arsenic concentration and creatinine-adjusted urinary arsenic concentration were simulated. As part of the evaluation, both water and dietary intakes of arsenic were estimated and used to generate the associated urine concentrations of the chemical in exposed populations.

RESULTS

When arsenic intake from water alone was considered, the results of the PBPK model underpredicted urinary arsenic concentrations for individuals with low levels of arsenic in drinking water and slightly overpredicted urinary arsenic concentrations in individuals with higher levels of arsenic in drinking water. When population-specific estimates of dietary intakes of iAs were included in exposures, the predictive value of the PBPK model was markedly improved, particularly at lower levels of arsenic intake.

CONCLUSIONS

Evaluations of this PBPK model illustrate its adequacy and usefulness for oral exposure reconstructions in human health risk assessment, particularly in individuals who are exposed to relatively low levels of arsenic in water or food. https://doi.org/10.1289/EHP3096.

Poultry Consumption and Arsenic Exposure in the U.S. Population

BACKGROUND

Arsenicals (roxarsone and nitarsone) used in poultry production likely increase inorganic arsenic (iAs), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), and roxarsone or nitarsone concentrations in poultry meat. However, the association between poultry intake and exposure to these arsenic species, as reflected in elevated urinary arsenic concentrations, is unknown.

OBJECTIVES

Our aim was to evaluate the association between 24-hr dietary recall of poultry consumption and arsenic exposure in the U.S. population. We hypothesized first, that poultry intake would be associated with higher urine arsenic concentrations and second, that the association between turkey intake and increased urine arsenic concentrations would be modified by season, reflecting seasonal use of nitarsone.

METHODS

We evaluated 3,329 participants ≥ 6 years old from the 2003-2010 National Health and Nutrition Examination Survey (NHANES) with urine arsenic available and undetectable urine arsenobetaine levels. Geometric mean ratios (GMR) of urine total arsenic and DMA were compared across increasing levels of poultry intake.

RESULTS

After adjustment, participants in the highest quartile of poultry consumption had urine total arsenic 1.12 (95% CI: 1.04, 1.22) and DMA 1.13 (95% CI: 1.06, 1.20) times higher than nonconsumers. During the fall/winter, participants in the highest quartile of turkey intake had urine total arsenic and DMA 1.17 (95% CI: 0.99, 1.39; p-trend = 0.02) and 1.13 (95% CI: 0.99, 1.30; p-trend = 0.03) times higher, respectively, than nonconsumers. Consumption of turkey during the past 24 hr was not associated with total arsenic or DMA during the spring/summer.

CONCLUSIONS

Poultry intake was associated with increased urine total arsenic and DMA in NHANES 2003-2010, reflecting arsenic exposure. Seasonally stratified analyses by poultry type provide strong suggestive evidence that the historical use of arsenic-based poultry drugs contributed to arsenic exposure in the U.S.

CITATION

Nigra AE, Nachman KE, Love DC, Grau-Perez M, Navas-Acien A. 2017. Poultry consumption and arsenic exposure in the U.S. Environ Health Perspect 125:370-377; http://dx.doi.org/10.1289/EHP351.

Modeling Population Exposures to Silver Nanoparticles Present in Consumer Products

Exposures of the general population to manufactured nanoparticles (MNPs) are expected to keep rising due to increasing use of MNPs in common consumer products (PEN 2014). The present study focuses on characterizing ambient and indoor population exposures to silver MNPs (nAg). For situations where detailed, case-specific exposure-related data are not available, as in the present study, a novel tiered modeling system, Prioritization/Ranking of Toxic Exposures with GIS (Geographic Information System) Extension (PRoTEGE), has been developed: it employs a product Life Cycle Analysis (LCA) approach coupled with basic human Life Stage Analysis (LSA) to characterize potential exposures to chemicals of current and emerging concern. The PRoTEGE system has been implemented for ambient and indoor environments, utilizing available MNP production, usage, and properties databases, along with laboratory measurements of potential personal exposures from consumer spray products containing nAg. Modeling of environmental and microenvironmental levels of MNPs employs Probabilistic Material Flow Analysis combined with product LCA to account for releases during manufacturing, transport, usage, disposal, etc. Human exposure and dose characterization further employs screening Microenvironmental Modeling and Intake Fraction methods combined with LSA for potentially exposed populations, to assess differences associated with gender, age, and demographics. Population distributions of intakes, estimated using the PRoTEGE framework, are consistent with published individual-based intake estimates, demonstrating that PRoTEGE is capable of capturing realistic exposure scenarios for the US population. Distributions of intakes are also used to calculate biologically-relevant population distributions of uptakes and target tissue doses through human airway dosimetry modeling that takes into account product MNP size distributions and age-relevant physiological parameters.

Arsenic speciation in total contents and bioaccessible fractions in atmospheric particles related to human intakes

Speciation of inorganic trivalent arsenicals (iAs(III)), inorganic pentavalent arsenicals (iAs(V)), monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA) in total arsenic (As) content and its bioaccessible fractions contained in road dust, household air-conditioning (AC) filter dust and PM2.5 was investigated. Inorganic As, especially iAs(V), was observed as the dominant species. Physiologically based extraction test (PBET), an in-vitro gastrointestinal method, was used to estimate the oral As bioaccessibility in coarse particles and the species present in the oral bioaccessible fraction. A composite lung simulating serum was used to mimic the pulmonary condition to extract the respiratory bioaccessible As and its species in PM2.5. Reduction of iAs(V) to iAs(III) occurred in both in-vitro gastrointestinal and lung simulating extraction models. The inorganic As species was the exclusive species for absorption through ingestion and inhalation of atmospheric particles, which was an important exposure route to inorganic As, in addition to drinking water and food consumption.

Diet and toenail arsenic concentrations in a New Hampshire population with arsenic-containing water

BACKGROUND

Limited data exist on the contribution of dietary sources of arsenic to an individual's total exposure, particularly in populations with exposure via drinking water. Here, the association between diet and toenail arsenic concentrations (a long-term biomarker of exposure) was evaluated for individuals with measured household tap water arsenic. Foods known to be high in arsenic, including rice and seafood, were of particular interest.

METHODS

Associations between toenail arsenic and consumption of 120 individual diet items were quantified using general linear models that also accounted for household tap water arsenic and potentially confounding factors (e.g., age, caloric intake, sex, smoking) (n = 852). As part of the analysis, we assessed whether associations between log-transformed toenail arsenic and each diet item differed between subjects with household drinking water arsenic concentrations <1 μg/L versus ≥1 μg/L.

RESULTS

As expected, toenail arsenic concentrations increased with household water arsenic concentrations. Among the foods known to be high in arsenic, no clear relationship between toenail arsenic and rice consumption was detected, but there was a positive association with consumption of dark meat fish, a category that includes tuna steaks, mackerel, salmon, sardines, bluefish, and swordfish. Positive associations between toenail arsenic and consumption of white wine, beer, and Brussels sprouts were also observed; these and most other associations were not modified by exposure via water. However, consumption of two foods cooked in water, beans/lentils and cooked oatmeal, was more strongly related to toenail arsenic among those with arsenic-containing drinking water (≥1 μg/L).

CONCLUSIONS

This study suggests that diet can be an important contributor to total arsenic exposure in U.S. populations regardless of arsenic concentrations in drinking water. Thus, dietary exposure to arsenic in the US warrants consideration as a potential health risk.

Quantifying children's aggregate (dietary and residential) exposure and dose to permethrin: application and evaluation of EPA's probabilistic SHEDS-Multimedia model

Reliable, evaluated human exposure and dose models are important for understanding the health risks from chemicals. A case study focusing on permethrin was conducted because of this insecticide's widespread use and potential health effects. SHEDS-Multimedia was applied to estimate US population permethrin exposures for 3- to 5-year-old children from residential, dietary, and combined exposure routes, using available dietary consumption data, food residue data, residential concentrations, and exposure factors. Sensitivity and uncertainty analyses were conducted to identify key factors, pathways, and research needs. Model evaluation was conducted using duplicate diet data and biomonitoring data from multiple field studies, and comparison to other models. Key exposure variables were consumption of spinach, lettuce, and cabbage; surface-to-skin transfer efficiency; hand mouthing frequency; fraction of hand mouthed; saliva removal efficiency; fraction of house treated; and usage frequency. For children in households using residential permethrin, the non-dietary exposure route was most important, and when all households were included, dietary exposure dominated. SHEDS-Multimedia model estimates compared well to real-world measurements data; this exposure assessment tool can enhance human health risk assessments and inform children's health research. The case study provides insights into children's aggregate exposures to permethrin and lays the foundation for a future cumulative pyrethroid pesticides risk assessment.

Incorporating nonchemical stressors into cumulative risk assessments

The role of nonchemical stressors in modulating the human health risk associated with chemical exposures is an area of increasing attention. On 9 March 2011, a workshop titled "Approaches for Incorporating Nonchemical Stressors into Cumulative Risk Assessment" took place during the 50th Anniversary Annual Society of Toxicology Meeting in Washington D.C. Objectives of the workshop included describing the current state of the science from various perspectives (i.e., regulatory, exposure, modeling, and risk assessment) and presenting expert opinions on currently available methods for incorporating nonchemical stressors into cumulative risk assessments. Herein, distinct frameworks for characterizing exposure to, joint effects of, and risk associated with chemical and nonchemical stressors are discussed.

Inorganic arsenic in Chinese food and its cancer risk

Even moderate arsenic exposure may lead to health problems, and thus quantifying inorganic arsenic (iAs) exposure from food for different population groups in China is essential. By analyzing the data from the China National Nutrition and Health Survey (CNNHS) and collecting reported values of iAs in major food groups, we developed a framework of calculating average iAs daily intake for different regions of China. Based on this framework, cancer risks from iAs in food was deterministically and probabilistically quantified. The article presents estimates for health risk due to the ingestion of food products contaminated with arsenic. Both per individual and for total population estimates were obtained. For the total population, daily iAs intake is around 42 μg day(-1), and rice is the largest contributor of total iAs intake accounting for about 60%. Incremental lifetime cancer risk from food iAs intake is 106 per 100,000 for adult individuals and the median population cancer risk is 177 per 100,000 varying between regions. Population in the Southern region has a higher cancer risk than that in the Northern region and the total population. Sensitive analysis indicated that cancer slope factor, ingestion rates of rice, aquatic products and iAs concentration in rice were the most relevant variables in the model, as indicated by their higher contribution to variance of the incremental lifetime cancer risk. We conclude that rice may be the largest contributor of iAs through food route for the Chinese people. The population from the South has greater cancer risk than that from the North and the whole population.

Assessing exposure to phthalates - the human biomonitoring approach

Some phthalates are developmental and reproductive toxicants in animals. Exposure to phthalates is considered to be potentially harmful to human health as well. Based on a comprehensive literature research, we present an overview of the sources of human phthalate exposure and results of exposure assessments with special focus on human biomonitoring data. Among the general population, there is widespread exposure to a number of phthalates. Foodstuff is the major source of phthalate exposure, particularly for the long-chain phthalates such as di(2-ethylhexyl) phthalate. For short-chain phthalates such as di-n-butyl-phthalate, additional pathways are of relevance. In general, children are exposed to higher phthalate doses than adults. Especially, high exposures can occur through some medications or medical devices. By comparing exposure data with existing limit values, one can also assess the risks associated with exposure to phthalates. Within the general population, some individuals exceed tolerable daily intake values for one or more phthalates. In high exposure groups, (intensive medical care, medications) tolerable daily intake transgressions can be substantial. Recent findings from animal studies suggest that a cumulative risk assessment for phthalates is warranted, and a cumulative exposure assessment to phthalates via human biomonitoring is a major step into this direction.

Probabilistic Modeling of Dietary Arsenic Exposure and Dose and Evaluation with 2003-2004 NHANES Data

BACKGROUND

Dietary exposure from food to toxic inorganic arsenic (iAs) in the general U.S. population has not been well studied.

OBJECTIVES

The goal of this research was to quantify dietary As exposure and analyze the major contributors to total As (tAs) and iAs. Another objective was to compare model predictions with observed data.

METHODS

Probabilistic exposure modeling for dietary As was conducted with the Stochastic Human Exposure and Dose Simulation Dietary (SHEDS-Dietary) model, based on data from the National Health and Nutrition Examination Survey. The dose modeling was conducted by combining the SHEDS-Dietary model with the MENTOR-3P (Modeling ENvironment for TOtal Risk with Physiologically Based Pharmacokinetic Modeling for Populations) system. Model evaluation was conducted via comparing exposure and dose-modeling predictions against duplicate diet data and biomarker measurements, respectively, for the same individuals.

RESULTS

The mean modeled tAs exposure from food is 0.38 microg/kg/day, which is approximately 14 times higher than the mean As exposures from the drinking water. The mean iAs exposure from food is 0.05 microg/kg/day (1.96 microg/day), which is approximately two times higher than the mean iAs exposures from the drinking water. The modeled exposure and dose estimates matched well with the duplicate diet data and measured As biomarkers. The major food contributors to iAs exposure were the following: vegetables (24%); fruit juices and fruits (18%); rice (17%); beer and wine (12%); and flour, corn, and wheat (11%). Approximately 10% of tAs exposure from foods is the toxic iAs form.

CONCLUSIONS

The general U.S. population may be exposed to tAs and iAs more from eating some foods than from drinking water. In addition, this model evaluation effort provides more confidence in the exposure assessment tools used.

Predicting residential exposure to phthalate plasticizer emitted from vinyl flooring: sensitivity, uncertainty, and implications for biomonitoring

BACKGROUND

Because of the ubiquitous nature of phthalates in the environment and the potential for adverse human health effects, an urgent need exists to identify the most important sources and pathways of exposure.

OBJECTIVES

Using emissions of di(2-ethylhexyl) phthalate (DEHP) from vinyl flooring (VF) as an illustrative example, we describe a fundamental approach that can be used to identify the important sources and pathways of exposure associated with phthalates in indoor material.

METHODS

We used a three-compartment model to estimate the emission rate of DEHP from VF and the evolving exposures via inhalation, dermal absorption, and oral ingestion of dust in a realistic indoor setting.

RESULTS

A sensitivity analysis indicates that the VF source characteristics (surface area and material-phase concentration of DEHP), as well as the external mass-transfer coefficient and ventilation rate, are important variables that influence the steady-state DEHP concentration and the resulting exposure. In addition, DEHP is sorbed by interior surfaces, and the associated surface area and surface/air partition coefficients strongly influence the time to steady state. The roughly 40-fold range in predicted exposure reveals the inherent difficulty in using biomonitoring to identify specific sources of exposure to phthalates in the general population.

CONCLUSIONS

The relatively simple dependence on source and chemical-specific transport parameters suggests that the mechanistic modeling approach could be extended to predict exposures arising from other sources of phthalates as well as additional sources of other semivolatile organic compounds (SVOCs) such as biocides and flame retardants. This modeling approach could also provide a relatively inexpensive way to quantify exposure to many of the SVOCs used in indoor materials and consumer products.

Advancing exposure characterization for chemical evaluation and risk assessment

A new generation of scientific tools has emerged to rapidly measure signals from cells, tissues, and organisms following exposure to chemicals. High-visibility efforts to apply these tools for efficient toxicity testing raise important research questions in exposure science. As vast quantities of data from high-throughput screening (HTS) in vitro toxicity assays become available, this new toxicity information must be translated to assess potential risks to human health from environmental exposures. Exposure information is required to link information on potential toxicity of environmental contaminants to real-world health outcomes. In the immediate term, tools are required to characterize and classify thousands of environmental chemicals in a rapid and efficient manner to prioritize testing and assess potential for risk to human health. Rapid risk assessment requires prioritization based on both hazard and exposure dimensions of the problem. To address these immediate needs within the context of longer term objectives for chemical evaluation and risk management, a translation framework is presented for incorporating toxicity and exposure information to inform public health decisions at both the individual and population levels. Examples of required exposure science contributions are presented with a focus on early advances in tools for modeling important links across the source-to-outcome paradigm. ExpoCast, a new U.S. Environmental Protection Agency (EPA) program aimed at developing novel approaches and metrics to screen and evaluate chemicals based on the potential for biologically relevant human exposures is introduced. The goal of ExpoCast is to advance characterization of exposure required to translate findings in computational toxicology to information that can be directly used to support exposure and risk assessment for decision making and improved public health.

ebTrack: an environmental bioinformatics system built upon ArrayTrack

ebTrack is being developed as an integrated bioinformatics system for environmental research and analysis by addressing the issues of integration, curation, management, first level analysis and interpretation of environmental and toxicological data from diverse sources. It is based on enhancements to the US FDA developed ArrayTrack™ system through additional analysis modules for gene expression data as well as through incorporation and linkages to modules for analysis of proteomic and metabonomic datasets that include tandem mass spectra. ebTrack uses a client-server architecture with the free and open source PostgreSQL as its database engine, and java tools for user interface, analysis, visualization, and web-based deployment. Several predictive tools that are critical for environmental health research are currently supported in ebTrack, including Significance Analysis of Microarray (SAM). Furthermore, new tools are under continuous integration, and interfaces to environmental health risk analysis tools are being developed in order to make ebTrack widely usable. These health risk analysis tools include the Modeling ENvironment for TOtal Risk studies (MENTOR) for source-to-dose exposure modeling and the DOse Response Information ANalysis system (DORIAN) for health outcome modeling. The design of ebTrack is presented in detail and steps involved in its application are summarized through an illustrative application.

Mechanistic modeling of emergency events: assessing the impact of hypothetical releases of anthrax

A modular system for source-to-dose-to-effect modeling analysis has been developed based on the modeling environment for total risk studies (MENTOR),((1)) and applied to study the impacts of hypothetical atmospheric releases of anthrax spores. The system, MENTOR-2E (MENTOR for Emergency Events), provides mechanistically consistent analysis of inhalation exposures for various release scenarios, while allowing consideration of specific susceptible subpopulations (such as the elderly) at the resolution of individual census tracts. The MENTOR-2E application presented here includes atmospheric dispersion modeling, statistically representative samples of individuals along with corresponding activity patterns, and population-based dosimetry modeling that accounts for activity and physiological variability. Two hypothetical release scenarios were simulated: a 100 g release of weaponized B. anthracis over a period of (a) one hour and (b) 10 hours, and the impact of these releases on population in the State of New Jersey was studied. Results were compared with those from simplified modeling of population dynamics (location, activities, etc.), and atmospheric dispersion of anthrax spores. The comparisons showed that in the two release scenarios simulated, each major approximation resulted in an overestimation of the number of probable infections by a factor of 5 to 10; these overestimations can have significant public health implications when preparing for and responding effectively to an actual release. This is in addition to uncertainties in dose-response modeling, which result in an additional factor of 5 to 10 variation in estimated casualties. The MENTOR-2E system has been developed in a modular fashion so that improvements in individual modules can be readily made without impacting the other modules, and provides a first step toward the development of models that can be used in supporting real-time decision making.